The literature has indicated that coronary artery disease is the single largest cause of death worldwide. Coronary artery disease is the narrowing of the lumen of the coronary artery, which supplies oxygen via blood to heart muscle. The lumen of the coronary artery varies in diameter. For example, a left main coronary artery lumen of a healthy adult individual is typically 4.5±0.5 mm in diameter and a distal left anterior descending coronary artery lumen is typically 1.9±0.4 mm.
One non-invasive technique to assess the narrowing of the coronary lumen, e.g. stenosis, is cardiac computed tomography angiography (CCTA). In CCTA, one or more three dimensional (3D) images, e.g. computed tomography (CT) images, of the coronary artery are used to identify and quantify the narrowing of the lumen. Another quantitative measure uses a difference in pressures with fractional flow reserve (FFR) simulations based on a 3D model of the lumen.
Visible imaging resolution or precision, such as with the CCTA imaging, is typically about 1.5 mm, e.g. one spatial dimension that differences in the image can accurately be resolved. Using images to determine the narrowing of a lumen that is less than three to four times the visible resolution impacts first, whether a narrowing is detected and second, the accuracy of a structure of the lumen segmented to quantify measurements affected by narrowing. Reconstruction algorithms typically smooth the image with a low-pass filter, which blurs the lumen boundary. In cases where the lumen diameter is smaller than the low-pass filter support, the smoothing process can cause segmentation algorithms to overestimate lumen diameter. Calcium deposits in an artery narrows the artery, which can cause blooming artifacts in imaging and in typical segmentation algorithms that mimic larger lumens than the true underlying lumens.